Intelligent Automation in Energy and Utilities

The Next Digital Wave

Intelligent automation and the smart, augmented utility of the future

As the world gasps for clean, safe, cheap, and reliable energy, demand from developing countries and the requirements of new usages rises, fueling a backlash against traditional, centralized power sources. As a result, reliance on renewable energy sources continues to grow, and the sector moves from regulation to innovation while its customers transform from passive consumers to demanding prosumers.

Artificial intelligence and automation in energy and utilities

Technologies such as automation and artificial intelligence will be instrumental in capitalizing on these shifts, offering the potential to save between $237 billion and $813 billion over the next three years. But are organizations poised to make a success of them?

In the new report from the Capgemini Research Institute, Intelligent Automation in Energy and Utilities: The next digital wave, we surveyed close to 530 business leaders in sector organizations that are experimenting with or already implementing intelligent automation solutions. We also analyzed more than 80 use cases, assessing their maturity, complexity, and the benefits on offer. We found that:

  • The sector has underestimated intelligent automation’s true potential.
  • Scaling-up initiatives is still a critical issue, though significant progress has been made in AI solutions.
  • Organizations are missing out on critical use cases that can deliver outsized benefits.

Energy and utilities digital transformation

Digitalization is the wave of the future for the energy and utilities sector. To transform into the smart, augmented utility that will prosper in it, organizations should focus on midstream and upstream activities and on new businesses, such as renewables and beyond the meter. However, they must be pragmatic and maximize ROI by re-engineering processes before they are implemented. Finally, they must curate a culture and mindset in which these technologies complement the workforce’s skills.

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Sound Bites

Abhijeet Bhandare, Chief Automation Officer of GE Power

We have a very clear filtering criteria defined for automation use cases. We have close to 200 automation ideas in pipeline, and on an average about 50% to 60% of them will be rejected. It is important to focus your attention on the remaining 50%, as they will give you the most value. And you must have the right criteria – whether it is value, efficiencies, cost savings or the opportunity cost.

Aidan O’Sullivan, Head of University College London’s Energy & AI Research

The proliferation of virtual assistants in homes, combined with data, could fundamentally disrupt the way we buy and use electricity. The integration of energy data with products like Alexa and Google Home may lead to AI home energy management systems where, for example, rather than turn on your washing machine yourself, you schedule it to run when the electricity price is going to be lower.

Morag Watson, Chief Digital Innovation Officer of BP

I often talk about artificial intelligence as augmented intelligence. It really is about bringing something else to the table, such that our experts and people can focus even more on the stuff they were trained to do and on the higher order stuff. I think that there could be a whole new class of jobs, and a whole new range of things to be done in the future, that we didn’t know existed.

Key Insights

15%

of energy and utilities organizations have been able to deploy multiple use cases at scale

47%

executives say that the cost savings of intelligent automation were under-estimated

52%

of energy and utilities organizations, in 2019, have deployed a few or multiple AI use cases

About the Capgemini Research Institute

Capgemini Research Institute

Capgemini’s #1 ranked in-house think tank on all things digital

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